Variance (un)explained: Experimental conditions and temporal dependencies explain similarly small proportions of reaction time variability in linear models of perceptual and cognitive tasks.

Authors

Tobias Heed (ORCID: https://orcid.org/0000-0001-5632-6091)
Christoph Kayser (ORCID: https://orcid.org/0000-0001-7362-5704)
Marlou Nadine Perquin (ORCID: https://orcid.org/0000-0001-9791-8202)

Institutions

Bielefeld University (DE)

Publication Details

Journal: Journal of Experimental Psychology General
Published: 2024-09-23
DOI: https://doi.org/10.1037/xge0001630
Citations: 6
Primary Topic: Neural Networks and Applications
Type: article
Field-Weighted Citation Impact: 1.74

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article

Variance (un)explained: Experimental conditions and temporal dependencies explain similarly small proportions of reaction time variability in linear models of perceptual and cognitive tasks.

Tobias Heed, Christoph Kayser, Marlou Nadine Perquin

Sep 23, 2024

6 citations

Journal of Experimental Psychology General

Neural Networks and Applications

1.74

article

Variance (un)explained: Experimental conditions and temporal dependencies explain similarly small proportions of reaction time variability in linear models of perceptual and cognitive tasks.

Tobias Heed, Christoph Kayser, Marlou Nadine Perquin

September 23, 2024article en

6 citations

Abstract

No abstract available for this paper.

Journal of Experimental Psychology GeneralVol. 153(12)

Bielefeld University (DE)

Openalex Percentile: Top 13%

Neural Networks and Applications

1.74

DOI Source OpenAlex

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Variance (un)explained: Experimental conditions and temporal dependencies explain similarly small proportions of reaction time variability in linear models of perceptual and cognitive tasks. — Tobias Heed, Christoph Kayser, et al. · Journal of Experimental Psychology General (2024) | TGRS Research Map | TGRS